The general objective of this study is to determine rural farmers’ access to agricultural information in the study area while the specific objectives of the study were to:

1. Describe the socio-economic characteristics of the respondents.

2. Examine the enterprise characteristics of the respondents.

3. Identify respondents’ sources of agricultural information.

4. Ascertain the respondents’ access to agricultural information.

5. Identify the respondents’ constraints in accessing agricultural information.

The following hypotheses stated in the null form were tested in this study:

Ho1: There is no significant relationship between socio-economic characteristics of the respondents and their access to agricultural information.

Ho2: There is no significant relationship between respondents’ sources of agricultural information and frequency of access.

This study was carried out in Ido Local government area of Oyo State between 12^th March and 25^th June 2013. The Local government happens to be the largest in the state with 14 prominent communities. It has land area of 986 km² and a population of 104,261 as at 2006 population census NPC [5] . The strategic location of the local government within the deciduous forest in the central part of Oyo State makes it one of the most viable areas for agriculture in the state. The climate of this area is tropical in nature and the vegetation is essentially of the rainforest type. The inhabitants of Ido-local government area are predominantly farmer cultivating both food and cash crops.

Simple random sampling technique was used for this study. The first stage involved the selection of 10 communities from the 14 communities in Ido-local government using simple random sampling technique. The second stage involved the selection of 12 rural farmers from each of the selected communities from the list of rural farmers in Ido local government area through extension workers using simple random sampling technique which gives a total sample size of 120 rural farmers for the study.

The data for this study were collected through both primary and secondary sources. The primary data were collected through interview schedule while secondary data entails the review of relevant literature to the study.

The variables for this study include rural farmers socio-economic characteristics (age, sex, marital status, level of education etc), enterprise characteristics which was elicited by asking the respondents to indicate their source of labour, source of finance from the options presented, farm size was measured by asking the respondents to estimate the farm size cultivated, aspects of farming respondents engaged with, farming experience etc.

Sources of Agricultural Information was measured by asking the respondents to state their source of Agricultural Information from a list of sources listed and frequency of use of those sources using a 3 point Likert-type scale of regularly, sometimes, never which were scored 3, 2, 1.

Access to Agricultural Information was captured by asking the respondents to indicate their access to various Agricultural Information listed using a 3 point Likert-type scale of regularly, sometimes, never with the score of 3, 2, 1 assigned to them respectively.

Constraints to access Agricultural information was measured by asking the respondents to response to the constraints they faced from the options stated which were classified as major, minor , not a constraint and score of 3, 2, 1 were assigned to them respectively.

Data collected was analysed using descriptive and inferential statistics. Descriptive statistics involved the use of frequency and percentages and inferential statistics involved the use of Pearson product moment correlation and chi-square. Hypothesis 1 was tested with chi-square and PPMC at 0.05 level of significance while Hypothesis 2 was tested using PPMC at 0.05 level of significance.

Table 1 shows that most of the respondents were within the age range of less than 30 years (31.7%), an indication of active and very young rural farmers were more involved in accessing agricultural information than middle and old ages rural farmers. Majority of the rural farmers (70%) were male, married (62.5%) and Christian religion (55.8%) was the popular religion among the respondents. Also, majority of the respondents (91.7%), (60.0%) were into farming as their secondary occupation and primary occupation respectively which has signified that farming is the major activity that is more pronounced among rural settlers. Further results shows that majority of the respondents (73.3%) had a family size of between 4 - 6 persons and 45.8% of them had adult education and earned income of less or equal to N10,000 which could be as a result of lack of rural farmers access to pertinent agricultural information that may assist them to increase their productivity.

Result of the findings presented in Table 2 indicated that the respondents (42.5%) depends on paid labour as their source of labour, 47.5% of them depend on association members as their source of finance and majority of

the respondents (83.3%) were involved in crop farming which determined the aspect of agricultural information rural farmers have access with. Findings also show that rural farmers (43.3%) of them had between 6 - 10 hectares of farmland, 62.5% of them had pond size of 100 - 500 meters square and 58.4% of them had between 6 - 10 years of farming experience which could have influenced rural farmers accessibility to agricultural information.

Respondents available sources of agricultural information and their frequency of use.

The sources of agricultural information available to farmers in the study area and the frequency of use is shown in Table 3 as majority (72.5%) of the rural farmers depend on the use of radio to access agricultural information regularly, 32.5% of the respondents use television regularly, 45.0% of the rural farmers depend on the use of their association to access agricultural information regularly while 2.5% of the rural farmers depend on their friends to access agricultural information regularly. The implication of this result shows that radio is the most popular, preferred and frequently used organs in accessing agricultural information by the rural farmers in this study area. This is in line with the work of Munyua [6] who stated that majority of farmers use radio as their major source of agricultural information, probably because it is portable and can be operated by anybody, and the cost of maintenance is very cheap as it was expressed in the work of Ozowa [7] that radio programmes are most efficient in communicating agricultural information to towns and villages.

The result of the study in Table 4 shows that 79.2% of the respondents access agricultural information on market regularly, 76.7% of the respondents access agricultural information on fertilizer application regularly, 72.5% of the respondents indicated their regular access on agricultural information on storage, 69.2% indicated their regular access on spacing and planting date, 68.3% of the respondents indicated their regular access on an im-

proved drying techniques, 50.8% indicated their regular access on improved method of weed control and seed varieties respectively.

Table 5 revealed that rural farmers (87.5%) opined that feedback problem was the major constraint in accessing agricultural information which implies that there is a gap between the rural farmers, extension officers and researchers in the process of accessing agricultural information. This is in line with the work of Idowu who asserted that there is a wide gap between farmers, extension workers and researcher.

Also, illiteracy was among the constraints the respondents were facing in accessing agricultural information

with 54.2% as major constraint which could be as a result of low level of education the rural farmers attained. Further result revealed that inconsistent in agricultural information was among the constraints the respondents were facing in accessing agricultural information with 48.3% as major constraint which could be attributed to poor extension services among the extension workers.

The result of the chi-square analysis in Table 6 shows that there was significant relationship between rural farmers’ sex, marital status, and their access to agricultural information (X² = 8.265, p = 0.004; X² = 16.420, p = 0.003; respectively). The implication is that sex of the farmer is related to their access to agricultural information but male farmers have more access to information than female farmers. With respects to marital status, married farmers have more access to agricultural information compared to other farmers in their category. Further result of chi-square analysis revealed that there was no significant relationship between rural farmers’ religion, level of education and access to agricultural information (X² = 0.657, p = 0.720; X² = 0.564, p = 0.605) (Table 7). Therefore, the null hypothesis was rejected with respect to sex, marital status but the hypothesis was accepted with respect to religion and level of education.

Further result of socio-economic characteristics of the respondents using PPMC revealed that age, household size were not significant (r = 0.113, p = 0.221; r = 0.023, p = 0.800 respectively) but the income of the rural farmers was significant (r = 0.229, p = 0.012) which implies that rural farmers with higher level of income will have better access to agricultural information when compared with farmers with low level of income.

Further result in Table 8 revealed that there was a correlation between respondents’ sources of agricultural information and access to agricultural information (r = 0.582, p = 0.000).

The implication of this is that rural farmers with various sources of agricultural information will have more access to agricultural information when compared it with respondents that were restricted with different sources of agricultural information.